Real-time adaptive child-robot interaction: Age and gender determination of children based on 3D body metrics

Abstract

Service robots employed in public spaces need to be equipped with specific sensing, reasoning and human-robot interaction capabilities to adapt their interaction style and thus effectively engage with a variety of users. In this paper we present a method used by an ubiquitous robotic system to gather 3D body metrics and use them to robustly estimate age and gender of previously unseen participants in real-world multi-party situations. We evaluate system's performance on 428 children volunteers and compare them with those obtainable with a state of the art software based on face analysis. This work demonstrates that even small number of biometrics can achieve good age and gender estimation results in perceptually challenging environments. Finally, this paper illustrates how the system is used to inform the online adaptation of the behavior of a humanoid robot.